Doctoral student in Data Representation and Machine Learning over Networks at KTH.

We are seeking 1-2 Doctoral students with a strong background and interest in Mathematics, Optimization, Machine Learning, and Wireless Networks.  Previous evident exposure to Optimization, either via courses or documented self study, is a must.

The PhD project will contribute to the development of the theoretical foundations of Efficient Data Representation and Machine Learning over future wireless networks. Beside providing the capacity for harvesting a massive amount of data, such networks will significantly reduce the run time by dividing the computational burden among multiple computational agents, being highly favorable for time-dependent and adaptive applications. However, these networks poses tremendous challenges for the success of Machine Learning methods.

The WASP PhD program in Electrical Engineering and Computer Sciences provides world class quality education, including a large list of graduate courses ensuring an in-depth development of relevant competences and skills.

This is a two-stage call. In the first phase, projects were applied for and evaluated. Approved projects then continued to this, the second phase, where each university open calls for PhD positions. Information about AI/MLX Collaboration Projects can be found in the initial call: https://wasp-sweden.org/positions/wasp-collaboration-projects-within-ai-mlx/

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